Genetic Algorithms

Holland's most famous invention was not a theory but a mechanism. A genetic algorithm maintains a population of candidate solutions, each encoded as a string of building blocks. The algorithm evaluates candidates against a fitness function, selects the most successful, and recombines their building blocks — crossing segments from one candidate with segments from another — to produce offspring inheriting characteristics from both parents. Occasional random mutations introduce novel building blocks. The cycle repeats across generations, and the population converges toward solutions better than anything a human designer could produce by hand, because the algorithm explores combinatorial spaces too vast for any individual mind to navigate. The algorithm has no model of the solution and no understanding of the problem. Its intelligence is entirely emergent, arising from variation, selection, and accumulation operating on building block populations.